Last Monday, before heading up to Dundee University to move my son into student halls, I had the opportunity to attend the launch of an excellent new resource at the University of Glasgow.
The team at the School of Education has developed the Toolkit for Reflecting on the Use of Digital and Artificial Intelligence (AI) Technologies in Learning and Teaching. Rather than promoting specific tools or offering a rigid compliance checklist, the toolkit encourages structured reflection, professional dialogue, and active enquiry through self-assessment activities, real-world case studies, and guided reflective frameworks. It supports reflection across various dimensions of technology use and can be used individually or collaboratively, with the flexibility to adapt to different educational settings.
It is structured into four parts that move from examining personal pedagogical assumptions to analyzing mock case studies and planning future lessons. By utilising established academic frameworks like SAMR, TPACK, and the Conversational Framework, the resource encourages a shift from mere technology adoption to evidence-informed reflection.
The materials also highlight ethical considerations, such as data privacy and accessibility, ensuring that tools serve human-centered learning goals.
Ultimately, the toolkit provides a staged scaffold for practitioner enquiry, helping teachers sustain a reflective digital practice as technology evolves.
It was good to meet some Education Scotland colleagues along at the launch and hear that they had been supportive in the development of this resource.
The toolkit has several clear strengths:
- Sensible progression: It thoughtfully steps staff through selecting suitable technology based on actual learning needs, asking grounded questions about tech and AI along the way.
- Solid pedagogical focus: It grounds learning design effectively, with a particularly useful focus on the ABC model.
- Open access: It is published as an Open Educational Resource (OER), making it widely accessible. #OpenScot
The overall approach is remarkably sound, and it is worth planning to use some of the slides and exercises with staff to help shape their approach to learning technology and AI. That said, to make the absolute most of it in practice, there are a few tweaks I'd make:
- Streamlining the activities: I’d likely cut down on some of the exercises. A few sections feel slightly wordy, and it can take a bit long to reach the practical next steps of selecting the right technology.
- Localising to institutional context: In an institutional setting, you need to explicitly point staff toward the specific tools supported by their institution. The toolkit omits this local layer to remain universally applicable, so I’d add that context back in.
- Critiquing misuse: It also presents a good opportunity to explore what might be missing, or address where educational technology and AI are being used inappropriately. Example I often use - a poor set of engineering lecturers being driven to distraction by an edtech trying to get them to adopt Powtoons of cuddily toys with powertools.
- Expanding case study scope: The team is currently expanding the case studies at the back. Right now, they are heavily focused on primary schools, which opens up a great opportunity for colleges and HE institutions to collaborate with the university to develop further sector-specific examples.
Ultimately, I’d take the core slides and checklists and adapt them to fit a specific institutional context. Overall, the resources in this pack are a valuable addition to the toolkit of both Learning Technology teams and staff developer leads.
There are a lot of resources appearing in this space. (digital learning support with a focus on AI) I didn't ask but was not sure where this resource fitted along side Glasgow University's lead on the Centre for Teaching Excellence and or work around digital learning appearing from the digital hub at Edinburgh University.
Event was timely as I was doing a sector wide presentation later in the week with an AI focus and I was able to include this resource in references.
There was a plug too for an 'International Symposium' on AI in summer 2027
If you work in Learning Technology or a Learning and Teaching Academy worth downloading the PDF - and with proper attribution for orginal underpinning work perhaps running your own local AI model to repurpose some of the slides and resources in this pack. My preferred model for this at moment is giving Notebook LM the PDF and asking it to create presentation slides that I can then edit.
Here is a first pass at creating presentation from the PDF using Notebook LM - it is far too 'glossy' I would never use a deck like this - but great indication of what Notebook LM can do in under a minute. Please note proper attribution.
Get Involved
Contribute Case Studies: If your college or university wants to contribute sector case studies, reach out to Dr. Mark Peart at the University of Glasgow School of Education.
